Evidence map›Paper›PMID 36711413›Full record

ArticleFrontiers in public health2022

Effectiveness of the graded transport mode for the intrahospital transport of critically ill patients: A retrospective study.

Lijing Ling, Xiaohua Xia, Hua Yuan, Shifang Liu, Zhiqiang Guo, Caihong Zhang, Jin Ma

Abstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Observational
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Lijing LingDepartment of Emergency Medicine, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, China.
Xiaohua XiaDepartment of Emergency Medicine, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, China.
Hua YuanDepartment of Emergency Medicine, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, China.
Shifang LiuDepartment of Emergency Medicine, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, China.
Zhiqiang GuoDepartment of Emergency Medicine, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, China.
Caihong ZhangDepartment of Emergency Medicine, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, China.
Jin MaDepartment of Emergency Medicine, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: The purpose of this study was to evaluate the effectiveness of the graded transport mode in the intrahospital transport (IHT) of critically ill patients. Methods: This is a retrospective study, including 800 patients and categorized them into control and observation groups. The control group included 420 critically ill patients who were transported Results: The observation group had significantly lower transport time and AE incidence rates than the control group. However, no significant differences were observed in terms of the length of stay and mortality rate between the two groups. Conclusion: The most notable merits of the graded transport mode in the IHT of critical care patients include the fact that it significantly reduces the incidence of AEs during IHT, shortens the transport time, and improves transport efficiency, thereby ensuring the safety of critically ill patients.

Indexed as

Critical IllnessIntensive Care UnitsCritical CareHumansRespiration, ArtificialRetrospective Studiesadverse eventscritically ill patientsemergency treatmentgraded transportintrahospital transport

Identifiers

PMID36711413
PMCPMC9880033

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.